A method of predicting visual detectability of low-velocity impact damage in composite structures based on logistic regression model  

作　　者：Fengyang JIANG Zhidong GUAN Zengshan LI Xiaodong WANG 

机构地区：[1]School of Aeronautic Science and Engineering,Beihang University,Beijing 100083,China

出　　处：《Chinese Journal of Aeronautics》2021年第1期296-308,共13页中国航空学报（英文版）

基　　金：supported by COMAC Beijing Aeronautical Science&Technology Research Institute。

摘　　要：This paper proposed a new method for quantitative assessment of visual detectability of damage based on logistic regression,using the Probability of Detection(POD)as a criterion.Experiments were performed to establish the massive hit/miss data of visual inspection.Authoritative investigations verified the reliability of the data.The prediction function concluded comprises more than one flaw size parameters,including the depth and diameter of the dents.The results show that the depth and diameter of the dents are pivotal for the evaluation of detectability;the type of detection,the detection distance,and the qualifications of personnel are critical external factors to be considered.This function,with an accuracy rate of nearly 85%,is capable of predicting the visual detection probability of impact damage under various detection environments,which will provide a reference for the damage tolerance design of composite materials and field maintenance in the NonDestructive Testing(NDT)field.

关 键 词：Composite materials Damage tolerance Machine learning NDT Logistic regression 

分 类 号：TB33[一般工业技术—材料科学与工程] V214.8[航空宇航科学与技术—航空宇航推进理论与工程]